Random Access in Low-Earth-Orbit Satellite Networks Under Multi-Satellite and Multi-Beam Scenarios

In recent years, the utilization of low Earth orbit (LEO) satellite networks for achieving global coverage in mobile communications has emerged as a prominent area of interest in industry development and research. With the proliferation of satellites in LEO satellite networks, users often find themselves within the overlapping coverage of multiple satellite beams. However, the current state of affairs fails to capitalize on the potential advantages offered by these overlapping coverage areas, despite the continuous growth in the number of users. Addressing the scenario where a substantial number of users simultaneously engage in random access within the coverage of multiple satellites employing multiple beams, this paper presents a novel LEO satellite random access selection algorithm based on evolutionary game theory. The algorithm takes into account factors such as the user’s channel condition, preamble signal power, and access success probability when determining whether to replace the current random access target satellite. By establishing an evolutionary game model between users and satellites, the algorithm aims to maximize the utility for both parties. Simulation experiments are conducted to demonstrate the effectiveness and stability of the Evolutionary Game Random Access (EGRA) algorithm. The results indicate that the algorithm significantly enhances the success rate of random access for users, reduces access delay, and mitigates the probability of collisions.